Length of stays in emergency departments varies considerably

Research Activities, June 2011, No. 370

Quality emergency department (ED) care is often defined by time spent in the ED by the patient. This can be broken down into three distinct periods: waiting room time, treatment time, and boarding time (waiting for an inpatient bed). Recently, researchers used quantile regression, a statistical method, to characterize service completion times for these different phases at four academic medical center EDs. They found that patient waiting and treatment times varied widely among the four institutions.

The study used data on all visits to each of the EDs over a period of 1 year. Patient volumes ranged from 50,000 to 62,000. Emergency room bed capacities also differed, from 26 beds at one hospital to 41 beds at another. In terms of patient characteristics, one ED treated a higher percentage of the uninsured (37 percent). Another hospital ED treated a higher percentage (45 percent) of low-acuity patients compared with the others.

Waiting room times were influenced by the day of the week, time of day, and patient acuity level. Median waiting room times ranged from 15 to 44 minutes. Time spent in the waiting room was most influenced by the patient's mode of arrival. Ambulance patients waited less time to be put in a room compared with other patients, but experienced longer treatment times. Significant predictors of treatment time included chief complaint and acuity level. Patients arriving at the ED with a psychiatric problem had the longest treatment times regardless of their acuity level.

The researchers' statistical approach demonstrated just how variable length of stay can be across a variety of ED environments. In the future, such statistical analysis can serve as the basis for redesigning EDs and patient flow procedures to improve care. The study was supported in part by the Agency for Healthcare Research and Quality (HS17957).

See "Characterizing waiting room time, treatment time, and boarding time in the emergency department using quantile regression," by Ru Ding, M.S., Melissa L. McCarthy, Sc.D., Jeffrey S. Desmond, M.D., and others in Academic Emergency Medicine 17(8), pp. 813-823, 2010.

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